Does Spike-Timing-Dependent Synaptic Plasticity Couple or Decouple Neurons Firing in Synchrony?

Spike synchronization is thought to have a constructive role for feature integration, attention, associative learning, and the formation of bidirectionally connected Hebbian cell assemblies. By contrast, theoretical studies on spike-timing-dependent plasticity (STDP) report an inherently decoupling influence of spike synchronization on synaptic connections of coactivated neurons. For example, bidirectional synaptic connections as found in cortical areas could be reproduced only by assuming realistic models of STDP and rate coding. We resolve this conflict by theoretical analysis and simulation of various simple and realistic STDP models that provide a more complete characterization of conditions when STDP leads to either coupling or decoupling of neurons firing in synchrony. In particular, we show that STDP consistently couples synchronized neurons if key model parameters are matched to physiological data: First, synaptic potentiation must be significantly stronger than synaptic depression for small (positive or negative) time lags between presynaptic and postsynaptic spikes. Second, spike synchronization must be sufficiently imprecise, for example, within a time window of 5-10 ms instead of 1 ms. Third, axonal propagation delays should not be much larger than dendritic delays. Under these assumptions synchronized neurons will be strongly coupled leading to a dominance of bidirectional synaptic connections even for simple STDP models and low mean firing rates at the level of spontaneous activity.

[1]  W. Gerstner,et al.  Connectivity reflects coding: a model of voltage-based STDP with homeostasis , 2010, Nature Neuroscience.

[2]  Andreas Knoblauch,et al.  Synaptic plasticity, conduction delays, and inter-areal phase relations of spike activity in a model of reciprocally connected areas , 2003, Neurocomputing.

[3]  L. Abbott,et al.  Competitive Hebbian learning through spike-timing-dependent synaptic plasticity , 2000, Nature Neuroscience.

[4]  Sen Song,et al.  Highly Nonrandom Features of Synaptic Connectivity in Local Cortical Circuits , 2005, PLoS biology.

[5]  Y. Dan,et al.  Spike timing-dependent plasticity: from synapse to perception. , 2006, Physiological reviews.

[6]  Jean-Pascal Pfister,et al.  STDP in Oscillatory Recurrent Networks: Theoretical Conditions for Desynchronization and Applications to Deep Brain Stimulation , 2010, Front. Comput. Neurosci..

[7]  C. Petersen,et al.  The Excitatory Neuronal Network of the C2 Barrel Column in Mouse Primary Somatosensory Cortex , 2009, Neuron.

[8]  J. Hopfield,et al.  All-or-none potentiation at CA3-CA1 synapses. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[9]  Haim Sompolinsky,et al.  Learning Input Correlations through Nonlinear Temporally Asymmetric Hebbian Plasticity , 2003, The Journal of Neuroscience.

[10]  C. Gray,et al.  Heterogeneity in the responses of adjacent neurons to natural stimuli in cat striate cortex. , 2007, Journal of neurophysiology.

[11]  Harvey A Swadlow,et al.  Information Flow along Neocortical Axons , 2000 .

[12]  Günther Palm,et al.  On Associative Memories , 1987 .

[13]  S. Laughlin,et al.  An Energy Budget for Signaling in the Grey Matter of the Brain , 2001, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[14]  R. Desimone,et al.  Modulation of Oscillatory Neuronal Synchronization by Selective Visual Attention , 2001, Science.

[15]  H. Markram,et al.  Physiology and anatomy of synaptic connections between thick tufted pyramidal neurones in the developing rat neocortex. , 1997, The Journal of physiology.

[16]  H. Markram,et al.  Regulation of Synaptic Efficacy by Coincidence of Postsynaptic APs and EPSPs , 1997, Science.

[17]  Henning Sprekeler,et al.  Inhibitory Plasticity Balances Excitation and Inhibition in Sensory Pathways and Memory Networks , 2011, Science.

[18]  M. Woodin,et al.  Spike-Timing Dependent Plasticity in Inhibitory Circuits , 2010, Front. Syn. Neurosci..

[19]  J. Knott The organization of behavior: A neuropsychological theory , 1951 .

[20]  Professor Moshe Abeles,et al.  Local Cortical Circuits , 1982, Studies of Brain Function.

[21]  D Marr,et al.  Simple memory: a theory for archicortex. , 1971, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[22]  Wulfram Gerstner,et al.  A neuronal learning rule for sub-millisecond temporal coding , 1996, Nature.

[23]  S. Wang,et al.  Graded bidirectional synaptic plasticity is composed of switch-like unitary events. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[24]  Nicolas Brunel,et al.  Dynamics of Sparsely Connected Networks of Excitatory and Inhibitory Spiking Neurons , 2000, Journal of Computational Neuroscience.

[25]  John P. Miller,et al.  Temporal encoding in nervous systems: A rigorous definition , 1995, Journal of Computational Neuroscience.

[26]  G. Bi,et al.  Temporal asymmetry in spike timing-dependent synaptic plasticity , 2002, Physiology & Behavior.

[27]  Wulfram Gerstner,et al.  Phenomenological models of synaptic plasticity based on spike timing , 2008, Biological Cybernetics.

[28]  L. Abbott,et al.  Neural network dynamics. , 2005, Annual review of neuroscience.

[29]  P. J. Sjöström,et al.  Rate, Timing, and Cooperativity Jointly Determine Cortical Synaptic Plasticity , 2001, Neuron.

[30]  Andreas Knoblauch,et al.  Pattern separation and synchronization in spiking associative memories and visual areas , 2001, Neural Networks.

[31]  Michael N. Shadlen,et al.  Noise, neural codes and cortical organization , 1994, Current Opinion in Neurobiology.

[32]  Friedemann Pulvermüller,et al.  The Neuroscience of Language: On Brain Circuits of Words and Serial Order , 2003 .

[33]  J. Montgomery,et al.  Discrete synaptic states define a major mechanism of synapse plasticity , 2004, Trends in Neurosciences.

[34]  Terrence J Sejnowski,et al.  Communication in Neuronal Networks , 2003, Science.

[35]  Günther Palm,et al.  Scene segmentation by spike synchronization in reciprocally connected visual areas. II. Global assemblies and synchronization on larger space and time scales , 2002, Biological Cybernetics.

[36]  Y. Dan,et al.  Spike-timing-dependent synaptic plasticity depends on dendritic location , 2005, Nature.

[37]  Andreas Knoblauch,et al.  Spike-timing-dependent synaptic plasticity can form "zero lag links" for cortical oscillations , 2004, Neurocomputing.

[38]  A. Pérez-Villalba Rhythms of the Brain, G. Buzsáki. Oxford University Press, Madison Avenue, New York (2006), Price: GB £42.00, p. 448, ISBN: 0-19-530106-4 , 2008 .

[39]  G. Palm Neural Assemblies , 1982, Studies of Brain Function.

[40]  M. Poo,et al.  Spike-Timing-Dependent Plasticity of Neocortical Excitatory Synapses on Inhibitory Interneurons Depends on Target Cell Type , 2007, The Journal of Neuroscience.

[41]  A. Lansner Associative memory models: from the cell-assembly theory to biophysically detailed cortex simulations , 2009, Trends in Neurosciences.

[42]  P. Pavlidis,et al.  Pair Recordings Reveal All-Silent Synaptic Connections and the Postsynaptic Expression of Long-Term Potentiation , 2001, Neuron.

[43]  J. Fell,et al.  The role of phase synchronization in memory processes , 2011, Nature Reviews Neuroscience.

[44]  E. Capaldi,et al.  The organization of behavior. , 1992, Journal of applied behavior analysis.

[45]  E. Bienenstock,et al.  Theory for the development of neuron selectivity: orientation specificity and binocular interaction in visual cortex , 1982, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[46]  B. Kampa,et al.  Calcium Spikes in Basal Dendrites of Layer 5 Pyramidal Neurons during Action Potential Bursts , 2006, The Journal of Neuroscience.

[47]  Markus Diesmann,et al.  Spike-Timing-Dependent Plasticity in Balanced Random Networks , 2007, Neural Computation.

[48]  Michael J. Jutras,et al.  Synchronous neural activity and memory formation , 2010, Current Opinion in Neurobiology.

[49]  A. Knoblauch THE ROLE OF STRUCTURAL PLASTICITY AND SYNAPTIC CONSOLIDATION FOR MEMORY AND AMNESIA IN A MODEL OF CORTICO-HIPPOCAMPAL INTERPLAY , 2009 .

[50]  M. DeWeese,et al.  Non-Gaussian Membrane Potential Dynamics Imply Sparse, Synchronous Activity in Auditory Cortex , 2006, The Journal of Neuroscience.

[51]  S. Levin Lectu re Notes in Biomathematics , 1983 .

[52]  Michael N. Shadlen,et al.  Synchrony Unbound A Critical Evaluation of the Temporal Binding Hypothesis , 1999, Neuron.

[53]  Evgueniy V. Lubenov,et al.  Decoupling through Synchrony in Neuronal Circuits with Propagation Delays , 2008, Neuron.

[54]  Daniel D. Lee,et al.  Equilibrium properties of temporally asymmetric Hebbian plasticity. , 2000, Physical review letters.

[55]  Roland Heim,et al.  Theoretical Approaches to Complex Systems , 1978 .

[56]  J. Bullier,et al.  Feedforward and feedback connections between areas V1 and V2 of the monkey have similar rapid conduction velocities. , 2001, Journal of neurophysiology.

[57]  S. Thorpe,et al.  Spike times make sense , 2005, Trends in Neurosciences.

[58]  M. Merello,et al.  Deep Brain Stimulation of the Subthalamic Nucleus for the Treatment of Parkinson's Disease , 2008 .

[59]  Y. Zuo,et al.  Experience-dependent structural plasticity in the cortex , 2011, Trends in Neurosciences.

[60]  R. Malinow,et al.  Direct measurement of quantal changes underlying long-term potentiation in CA1 hippocampus , 1992, Neuron.

[61]  Y Watanabe,et al.  Properties of Horizontal and Vertical Inputs to Pyramidal Cells in the Superficial Layers of the Cat Visual Cortex , 2000, The Journal of Neuroscience.

[62]  Günther Palm,et al.  Cell assemblies in the cerebral cortex , 2014, Biological Cybernetics.

[63]  P. Lennie The Cost of Cortical Computation , 2003, Current Biology.

[64]  W Singer,et al.  Visual feature integration and the temporal correlation hypothesis. , 1995, Annual review of neuroscience.

[65]  Eugene M. Izhikevich,et al.  Relating STDP to BCM , 2003, Neural Computation.

[66]  R. Eckhorn,et al.  Flexible cortical gamma-band correlations suggest neural principles of visual processing , 2001 .

[67]  Gèunther Palm,et al.  Neural Assemblies: An Alternative Approach to Artificial Intelligence , 1982 .

[68]  David B. Grayden,et al.  Spike-Timing-Dependent Plasticity: The Relationship to Rate-Based Learning for Models with Weight Dynamics Determined by a Stable Fixed Point , 2004, Neural Computation.

[69]  David W. Nauen,et al.  Coactivation and timing-dependent integration of synaptic potentiation and depression , 2005, Nature Neuroscience.

[70]  Andreas Knoblauch,et al.  Neural Associative Memory with Optimal Bayesian Learning , 2011, Neural Computation.

[71]  Isaac Meilijson,et al.  Distributed synchrony in a cell assembly of spiking neurons , 2001, Neural Networks.

[72]  H. Markram,et al.  Interneurons of the neocortical inhibitory system , 2004, Nature Reviews Neuroscience.

[73]  L. Abbott,et al.  Cortical Development and Remapping through Spike Timing-Dependent Plasticity , 2001, Neuron.

[74]  K. Svoboda,et al.  Experience-dependent structural synaptic plasticity in the mammalian brain , 2009, Nature Reviews Neuroscience.

[75]  Y. Dan,et al.  Spike-timing-dependent synaptic modification induced by natural spike trains , 2002, Nature.

[76]  György Buzsáki,et al.  Neural Syntax: Cell Assemblies, Synapsembles, and Readers , 2010, Neuron.

[77]  Guo-Qiang Bi,et al.  Spatiotemporal specificity of synaptic plasticity: cellular rules and mechanisms , 2002, Biological Cybernetics.

[78]  W. Gerstner,et al.  Triplets of Spikes in a Model of Spike Timing-Dependent Plasticity , 2006, The Journal of Neuroscience.

[79]  J J Hopfield,et al.  Neural networks and physical systems with emergent collective computational abilities. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

[80]  Günther Palm,et al.  Scene segmentation by spike synchronization in reciprocally connected visual areas. I. Local effects of cortical feedback , 2002, Biological Cybernetics.

[81]  Jason Wolfe,et al.  Sparse temporal coding of elementary tactile features during active whisker sensation , 2009, Nature Neuroscience.

[82]  Günther Palm,et al.  Memory Capacities for Synaptic and Structural Plasticity G ¨ Unther Palm , 2022 .

[83]  Ad Aertsen,et al.  Stable propagation of synchronous spiking in cortical neural networks , 1999, Nature.

[84]  Mark C. W. van Rossum,et al.  Stable Hebbian Learning from Spike Timing-Dependent Plasticity , 2000, The Journal of Neuroscience.

[85]  Christoph Braun,et al.  Coherence of gamma-band EEG activity as a basis for associative learning , 1999, Nature.

[86]  G. Bi,et al.  Synaptic Modifications in Cultured Hippocampal Neurons: Dependence on Spike Timing, Synaptic Strength, and Postsynaptic Cell Type , 1998, The Journal of Neuroscience.